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<article xsi:noNamespaceSchemaLocation="http://jats.nlm.nih.gov/publishing/1.1/xsd/JATS-journalpublishing1-mathml3.xsd" dtd-version="1.1" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"><front><journal-meta><journal-id journal-id-type="publisher-id">erd</journal-id><journal-title-group><journal-title>Education Reform and Development</journal-title></journal-title-group><issn>2652-5364</issn><eissn>2652-5372</eissn><publisher><publisher-name>Bio-Byword Scientific Publishing Pty. Ltd.</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.26689/erd.v8i7.15914</article-id><article-categories><subj-group subj-group-type="heading"><subject>Article</subject></subj-group></article-categories><title>Research on Practical Teaching for Big Data Majors in the Era of Artificial Intelligence</title><url>https://artdesignp.com/journal/erd/8/7/10.26689/erd.v8i7.15914</url><author>LinGuoyu,FanBaozhu,ChenZibo</author><pub-date pub-type="publication-year"><year>2026</year></pub-date><volume>8</volume><issue>7</issue><history><date date-type="pub"><published-time>2026-08-13</published-time></date></history><abstract>Against the backdrop of artificial intelligence and digital economy development, practical teaching for big data majors needs to shift its focus from knowledge transmission to competency cultivation. At present, prominent problems including outdated teaching content and insufficient practical training remain prevalent. To address these issues, this paper proposes AI-enabled teaching reforms: constructing an “AI + Knowledge Graph” intelligent teaching system, building intelligent practical training environments, advancing project-driven teaching and the integration of “posts, courses, competitions, certificates and innovation”, deepening industry-education integration, and establishing a closed-loop evaluation system. These measures will drive scenario-based and personalized teaching transformation, strengthen students’ engineering practice and problem-solving capabilities, and lay solid foundations for the cultivation of application-oriented talents.</abstract><keywords/></article-meta></front><body/><back><ref-list><ref id="B1" content-type="article"><label>1</label><element-citation publication-type="journal"><p>Wang S, Wang F, Zhu Z, Wang J, Tran T, Du Z, 2024, Artificial Intelligence in Education: A Systematic Literature Review. 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